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delete blank cells
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‎docs/source/tutorials/circuit_qudit_basics.ipynb‎

Lines changed: 83 additions & 92 deletions
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@@ -38,20 +38,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "8f2d9565",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:32:59.941117Z",
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"start_time": "2025-09-10T10:32:58.690552Z"
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}
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},
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"source": [
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"import tensorcircuit as tc\n",
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"from tensorcircuit.quditcircuit import QuditCircuit\n",
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"\n",
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"tc.set_backend(\"numpy\") # or \"jax\", \"tensorflow\", \"pytorch\"\n",
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"print(\"tensorcircuit version:\", tc.__version__)"
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],
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"outputs": [
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{
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"name": "stdout",
@@ -61,7 +55,13 @@
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]
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}
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],
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"execution_count": 1
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"source": [
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"import tensorcircuit as tc\n",
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"from tensorcircuit.quditcircuit import QuditCircuit\n",
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"\n",
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"tc.set_backend(\"numpy\") # or \"jax\", \"tensorflow\", \"pytorch\"\n",
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"print(\"tensorcircuit version:\", tc.__version__)"
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]
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},
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{
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"cell_type": "markdown",
@@ -76,21 +76,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "3fa13efe",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:00.001551Z",
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"start_time": "2025-09-10T10:32:59.998454Z"
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}
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},
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"source": [
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"c = QuditCircuit(nqudits=1, dim=13)\n",
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"c.h(0) # generalized Hadamard on the only qudit\n",
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"psi = c.wavefunction() # state vector of length 13^1 = 13\n",
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"probs = c.probability() # probability vector (length 3)\n",
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"print(r\"\\psi:\", psi)\n",
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"print(\"P:\", probs)"
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],
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"outputs": [
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{
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"name": "stdout",
@@ -105,7 +98,14 @@
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]
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}
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],
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"execution_count": 2
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"source": [
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"c = QuditCircuit(nqudits=1, dim=13)\n",
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"c.h(0) # generalized Hadamard on the only qudit\n",
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"psi = c.wavefunction() # state vector of length 13^1 = 13\n",
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"probs = c.probability() # probability vector (length 3)\n",
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"print(r\"\\psi:\", psi)\n",
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"print(\"P:\", probs)"
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]
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},
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{
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"cell_type": "markdown",
@@ -122,21 +122,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "c53a755e",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:00.018234Z",
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"start_time": "2025-09-10T10:33:00.014110Z"
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}
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},
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"source": [
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"cq = QuditCircuit(nqudits=2, dim=3) # two qutrits\n",
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"cq.h(0) # superpose control\n",
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"cq.csum(0, 1) # qudit CNOT analog (control=0, target=1)\n",
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"psi = cq.wavefunction()\n",
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"probs = cq.probability()\n",
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"print(r\"|\\psi|^2 (length 3^2=9):\", probs)"
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],
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"outputs": [
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{
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"name": "stdout",
@@ -147,7 +140,14 @@
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]
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}
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],
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"execution_count": 3
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"source": [
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"cq = QuditCircuit(nqudits=2, dim=3) # two qutrits\n",
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"cq.h(0) # superpose control\n",
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"cq.csum(0, 1) # qudit CNOT analog (control=0, target=1)\n",
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"psi = cq.wavefunction()\n",
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"probs = cq.probability()\n",
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"print(r\"|\\psi|^2 (length 3^2=9):\", probs)"
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]
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},
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{
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"cell_type": "markdown",
@@ -162,17 +162,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "6542deab",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:00.335589Z",
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"start_time": "2025-09-10T10:33:00.031885Z"
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}
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},
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"source": [
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"samples = cq.sample(batch=512, format=\"count_dict_bin\") # e.g., '00', '11', '22'\n",
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"samples"
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],
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"outputs": [
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{
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"data": {
@@ -185,7 +182,10 @@
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"output_type": "execute_result"
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}
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],
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"execution_count": 4
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"source": [
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"samples = cq.sample(batch=512, format=\"count_dict_bin\") # e.g., '00', '11', '22'\n",
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"samples"
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]
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},
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{
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"cell_type": "markdown",
@@ -206,24 +206,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "e4e2b769",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:00.350793Z",
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"start_time": "2025-09-10T10:33:00.346566Z"
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}
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},
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"source": [
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"import numpy as np\n",
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"\n",
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"c = QuditCircuit(nqudits=1, dim=5) # a ququint\n",
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"c.h(0) # start in equal superposition\n",
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"c.rx(0, theta=np.pi / 3, j=1, k=3) # rotate levels 1 and 3\n",
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"c.rz(0, theta=np.pi / 5, j=4) # add a phase to level 4\n",
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"psi = c.wavefunction()\n",
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"probs = c.probability()\n",
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"psi, probs"
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],
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"outputs": [
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{
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"data": {
@@ -240,7 +230,17 @@
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"output_type": "execute_result"
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}
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],
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"execution_count": 5
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"source": [
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"import numpy as np\n",
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"\n",
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"c = QuditCircuit(nqudits=1, dim=5) # a ququint\n",
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"c.h(0) # start in equal superposition\n",
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"c.rx(0, theta=np.pi / 3, j=1, k=3) # rotate levels 1 and 3\n",
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"c.rz(0, theta=np.pi / 5, j=4) # add a phase to level 4\n",
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"psi = c.wavefunction()\n",
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"probs = c.probability()\n",
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"psi, probs"
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]
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},
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{
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"cell_type": "markdown",
@@ -260,21 +260,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "a56be75e",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:00.361091Z",
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"start_time": "2025-09-10T10:33:00.357370Z"
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}
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},
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"source": [
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"c2 = QuditCircuit(nqudits=2, dim=4) # two ququarts\n",
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"c2.h(0)\n",
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"c2.h(1)\n",
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"c2.rxx(0, 1, theta=np.pi / 4, j1=0, k1=2, j2=1, k2=3)\n",
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"c2.rzz(0, 1, theta=np.pi / 7, j1=0, k1=1, j2=0, k2=1)\n",
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"c2.probability()"
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],
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"outputs": [
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{
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"data": {
@@ -289,7 +282,14 @@
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"output_type": "execute_result"
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}
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],
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"execution_count": 6
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"source": [
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"c2 = QuditCircuit(nqudits=2, dim=4) # two ququarts\n",
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"c2.h(0)\n",
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"c2.h(1)\n",
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"c2.rxx(0, 1, theta=np.pi / 4, j1=0, k1=2, j2=1, k2=3)\n",
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"c2.rzz(0, 1, theta=np.pi / 7, j1=0, k1=1, j2=0, k2=1)\n",
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"c2.probability()"
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]
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},
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{
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"cell_type": "markdown",
@@ -304,23 +304,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "fe4ed499",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:00.372256Z",
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"start_time": "2025-09-10T10:33:00.367671Z"
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}
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},
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"source": [
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"# Example: build a diagonal operator on a single qutrit (dim=3)\n",
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"import numpy as np\n",
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"\n",
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"c = QuditCircuit(1, dim=3)\n",
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"c.h(0)\n",
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"op = np.diag([0.0, 0.5, 1.0]) # acts on subspace levels 0,1,2\n",
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"expval = c.expectation((op, [0]))\n",
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"expval"
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],
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"outputs": [
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{
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"data": {
@@ -333,36 +324,37 @@
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"output_type": "execute_result"
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}
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],
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"execution_count": 7
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"source": [
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"# Example: build a diagonal operator on a single qutrit (dim=3)\n",
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"import numpy as np\n",
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"\n",
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"c = QuditCircuit(1, dim=3)\n",
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"c.h(0)\n",
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"op = np.diag([0.0, 0.5, 1.0]) # acts on subspace levels 0,1,2\n",
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"expval = c.expectation((op, [0]))\n",
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"expval"
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]
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"id": "648ee02776427b3c",
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"metadata": {},
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"source": [
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"### Apply Arbitrary Gate\n",
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"\n",
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"Just directly using ``any`` API by feeding the corresponding unitary"
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],
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"id": "648ee02776427b3c"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "4d73e00b952f2ac4",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:14.972605Z",
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"start_time": "2025-09-10T10:33:00.385060Z"
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}
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},
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"cell_type": "code",
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"source": [
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"d = 36\n",
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"c = tc.QuditCircuit(2, dim=d)\n",
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"h_matrix = tc.quditgates.h_matrix_func(d)\n",
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"c.any(0, unitary=h_matrix)\n",
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"csum_matrix = tc.quditgates.csum_matrix_func(d)\n",
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"c.any(0, 1, unitary=csum_matrix)\n",
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"c.sample(1024, format=\"count_dict_bin\")"
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],
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"id": "4d73e00b952f2ac4",
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"outputs": [
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{
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"data": {
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"output_type": "execute_result"
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}
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],
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"execution_count": 8
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"source": [
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"d = 36\n",
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"c = tc.QuditCircuit(2, dim=d)\n",
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"h_matrix = tc.quditgates.h_matrix_func(d)\n",
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"c.any(0, unitary=h_matrix)\n",
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"csum_matrix = tc.quditgates.csum_matrix_func(d)\n",
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"c.any(0, 1, unitary=csum_matrix)\n",
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"c.sample(1024, format=\"count_dict_bin\")"
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]
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},
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{
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"cell_type": "markdown",
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"\n",
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"All the functions are similar to the `tc.Circuit`\n"
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]
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-09-10T10:33:14.985131Z",
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"start_time": "2025-09-10T10:33:14.983579Z"
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}
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},
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"cell_type": "code",
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"source": "",
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"id": "9a33f318814fa510",
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"outputs": [],
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"execution_count": null
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}
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],
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"metadata": {},
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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